AI-generated reporting significantly reduces radiologists' reading times and increases report acceptability over time.
Key Details
- 1Study published in JACR evaluated AI-generated reports for chest X-rays.
- 2Researchers used Kakao Brain’s KARA-CXR model on a dataset of 756 radiographs.
- 3Five radiologists generated preliminary AI reports; two assessed acceptability and need for revisions.
- 4Human approval rates of AI-generated reports increased, indicating growing trust.
- 5Experts call for further study into improving preliminary AI reports and their impact on diagnostics.
Why It Matters
Streamlining reporting with AI could improve radiologist efficiency and address workforce pressures. Increased acceptability suggests AI integration is advancing, but accuracy and clinical impact remain focus areas for future research.
Source
Radiology Business
Related News
•AuntMinnie
Study: Computer Vision Models Best LLMs in Chest CT Breast Abnormality Detection
Computer vision models (CVMs) surpass large language models (LLMs) in accurately labeling incidental breast abnormalities on chest CT scans.
•Cardiovascular Business
Radiology Maintains Lead in FDA-Cleared AI Algorithms, Cardiology Follows
Radiology remains the top specialty for FDA-cleared AI, with cardiology as a strong second, particularly in cardiovascular imaging.
•AuntMinnie
Deep Learning Models Rival Radiologists for Pancreatic Cancer Detection on CT
Deep-learning models achieved comparable or superior accuracy to experienced radiologists in detecting pancreatic cancer on CT scans, especially for small tumors.